類Locusbots系統於分區揀貨倉庫之兩種揀貨機器人作業流程的比較研究

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葉彥輝(Yen-Hui Yeh) 查詢紙本館藏

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類Locusbots系統於分區揀貨倉庫之兩種揀貨機器人作業流程的比較研究

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摘要(中)

近年來，資訊科技的迅速發展和行動網絡的普及使得電子商務成為市場主流，這也帶來了「少量、多樣化」的市場需求趨勢。這樣的轉變不僅增加了物流中心的作業難度，尤其在揀貨作業方面更為明顯。根據De Koster et al.（2007）的研究顯示，物流中心目前仍然以勞力為主，揀貨作業成本相當高昂，佔總成本的50%以上。為因應這樣的市場環境，引入自動化設備並合理規劃揀貨策略成為提升物流中心成本、產能和效率的重要關鍵。
類Locusbots系統的優勢在於其可靈活增減揀貨機器人的特性，有效應對訂單淡旺季的挑戰。該系統採用動態路徑規劃，即時更新揀貨環境狀態，巧妙避開各種障礙物，並計劃最優的揀貨路徑。此外，在類Locusbots系統中，揀貨員不需在倉庫中四處移動，只需待在指定揀貨區域，由揀貨機器人運送訂單和揀貨箱，使揀貨員能夠專注進行揀貨作業。這不僅能降低人力成本，同時提高揀貨作業的效率和準確性。
基於上述理由，本研究聚焦於類Locusbots系統中的揀貨策略，將一物流揀貨倉庫區分為多個揀貨區塊（Block）數相同的揀貨區域（Zone），對「Robot的揀貨區域（Zone）選擇問題」與「Robot的揀貨區塊（Block）選擇問題」分別數個法則，並提出兩種同時考慮了上述兩個問題的不同揀貨流程，期望透過本研究的模擬與分析，找出最佳的揀貨策略組合以及揀貨流程。

摘要(英)

In recent years, the rapid development of information technology and the proliferation of mobile networks have made e-commerce the mainstream market. This has also brought about a trend of "small quantities, diverse varieties" in market demand. Such a shift not only increases the operational difficulty of logistics centers, but it is particularly evident in the picking operations. According to the research by De Koster et al. (2007), logistics centers are still predominantly labor-intensive, and the cost of picking operations is quite high, accounting for more than 50% of the total cost. To cope with this market environment, introducing automated equipment and reasonably planning picking strategies have become key factors in improving the cost, capacity, and efficiency of logistics centers.

The advantage of systems like LocusBots lies in their ability to flexibly increase or decrease the number of picking robots, effectively meeting the challenges of order fluctuations during peak and off-peak seasons. This system adopts dynamic path planning, which updates the picking environment status in real-time, skillfully avoids various obstacles, and plans the optimal picking path. Moreover, in a LocusBots-like system, pickers do not need to move around the warehouse; they only need to stay in designated picking zones. The picking robots transport orders and picking bins, allowing pickers to focus solely on the picking operations. This not only reduces labor costs but also improves the efficiency and accuracy of picking operations.

Based on the above reasons, this study focuses on the picking strategies in systems like LocusBots. It divides a logistics picking warehouse into several picking blocks (Blocks) and an equal number of picking zones (Zones). The study formulates several rules for the "Robot’s Zone Selection Problem" and the "Robot’s Block Selection Problem," and proposes two different picking processes that consider both of these issues simultaneously. Through simulation and analysis, this research aims to identify the optimal combination of picking strategies and processes.

關鍵字(中)

★ 物流中心
★ Locusbots系統
★ 揀貨機器人
★ 訂單選取法則
★ Robot的Zone選取法則
★ Robot的Block選取法則

關鍵字(英)

★ Logistics center
★ Locusbots system
★ Picking robots
★ Order selection rules
★ Robot′s zone selection rules
★ Robot′s block selection rules

論文目次

目錄
摘要 i
目錄 ii
圖目錄 v
表目錄 vi
第一章緒論 1
1.1研究背景 1
1.2研究動機 2
1.3研究目的 3
1.4研究環境 4
1.5論文架構 6
第二章文獻探討 9
2.1 Locusbots 系統（Locusbots System） 10
2.1.1 Locusbots系統環境與作業流程 12
2.1.2 Locusbots設備介紹 13
2.2 物流（Logistics） 17
2.2.1 物流的定義（Logistics definition） 17
2.2.2 物流中心介紹（Distribution centre introduction） 18
2.3 倉儲規劃（Warehouse planning） 20
2.3.1 倉儲設計（Warehouse design） 20
2.3.2 走道設計（Aisle design） 21
2.4 揀貨作業規劃（Picking operation planning） 23
2.4.1 揀貨方法（Picking method） 23
2.4.2 揀貨政策（Picking policy） 24
2.4.3揀貨路徑策略（Picking routing strategy） 27
2.4.4揀貨作業績效評估指標（Picking operation performance evaluation indicator） 30
2.5 Robot 派車法則（Robot dispatching rule） 30
2.5.1 單屬性派車法則（Single attribute dispatching rule） 31
2.5.2 多屬性派車法則（Multiple attribute dispatching rule） 33
第三章研究方法 34
3.1 Locusbots作業流程介紹 34
3.2 Locusbots作業流程之符號及變數定義 36
3.3 Locusbots系統各揀貨作業流程說明 37
3.3.1 揀貨機器人（Picking Robot）的揀貨作業流程 38
3.3.1.1類Locusbots系統的揀貨機器人之揀貨作業流程Type-I 38
3.3.1.2類Locusbots系統的揀貨機器人之揀貨作業流程圖Type-II 41
3.3.2 揀貨人員（Picker）的揀貨作業流程 44
3.4各研究問題之方法整理 46
3.5研究環境說明 51
3.6訂單選取問題 52
3.6.1隨機選取法 52
3.7 Robot的Zone選取法則（決定Robot該前往哪一個Zone） 53
3.7.1隨機選取法 53
3.7.2最短旅行距離法 53
3.7.3有最多待揀品項數的Zone優先法 55
3.7.4有最少待揀品項數的Zone優先法 56
3.7.5有最多待拜訪Block的Zone優先法 57
3.7.6有最少待拜訪Block的Zone優先法 58
3.8 Robot的Block選取法則（決定Robot該前往哪一個Block） 59
3.8.1隨機選擇法 59
3.8.2最短旅行距離法 59
3.8.3有最多待揀品項數的Block優先法 61
3.8.4有最少待揀品項數的Block優先法 62
3.8.5有最多正在揀貨Robot的Block優先法 63
3.8.6有最少正在揀貨Robot的Block優先法 64
3.9 揀貨人員的Block選取問題 65
3.9.1隨機選擇法 65
3.10揀貨人員Robot的選取問題（揀貨人員優先處理哪一台Robot） 65
3.10.1隨機選擇法 66
第四章模擬實驗與分析 67
4.1 模擬實驗設計 67
4.1.1 揀貨環境設定 67
4.1.2 實驗訂單設定 68
4.1.3 揀貨環境假設 69
4.1.4 績效評估指標 70
4.2 統計分析 71
4.2.1 分析說明 73
4.2.2 依「揀貨系統總執行時間（TST）」為績效評估指標 73
4.2.3 依「訂單在系統內總時間（TTIS）」為績效評估指標 88
4.3 實驗結論 103
第五章研究結論與建議 105
5.1 研究結論 105
5.2 未來研究建議 107
參考文獻 109
中文文獻 109
英文文獻 112

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指導教授

何應欽(Ying-Chin Ho)

審核日期

2024-7-26

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